Model-based monotonic improvement, as proven by [1]}, can be achieved when learning the dynamics model together with the policy. Namely, the authors give an upper-bound in the performance gain obtained when applying the learned policy to the learned dynamics model, compared to applying it on the real MDP (i.e. the true dynamics). Their finding is summarized in the following lemma.
